A SYSTEMATIC READING IN STATISTICAL TRANSLATION: FROM THE STATISTICAL MACHINE TRANSLATION TO THE NEURAL TRANSLATION MODELS.

Achieving high accuracy in automatic translation tasks has been one of the challenging goals for researchers in the area of machine translation since decades. Thus, the eagerness of exploring new possible ways to improve machine translation was always the matter for researchers in the field. Automat...

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Main Authors: Zakaria El Maazouzi, Badr Eddine EL Mohajir, Mohammed Al Achhab
Format: Article
Language:English
Published: UUM Press 2017-10-01
Series:Journal of ICT
Online Access:https://www.scienceopen.com/document?vid=83e44e0b-765e-483d-b050-4d82cb5930d6
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author Zakaria El Maazouzi
Badr Eddine EL Mohajir
Mohammed Al Achhab
author_facet Zakaria El Maazouzi
Badr Eddine EL Mohajir
Mohammed Al Achhab
author_sort Zakaria El Maazouzi
collection DOAJ
description Achieving high accuracy in automatic translation tasks has been one of the challenging goals for researchers in the area of machine translation since decades. Thus, the eagerness of exploring new possible ways to improve machine translation was always the matter for researchers in the field. Automatic translation as a key application in the natural language processing domain has developed many approaches, namely statistical machine translation and recently neural machine translation that improved largely the translation quality especially for Latin languages. They have even made it possible for the translation of some language pairs to approach human translation quality. In this paper, we present a survey of the state of the art of statistical translation, where we describe the different existing methodologies, and we overview the recent research studies while pointing out the main strengths and limitations of the different approaches.
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spelling doaj.art-837c0720d5324db6b721220f27ad0e512022-12-21T23:16:14ZengUUM PressJournal of ICT1675-414X2017-10-0110.32890/jict2017.16.2.8239A SYSTEMATIC READING IN STATISTICAL TRANSLATION: FROM THE STATISTICAL MACHINE TRANSLATION TO THE NEURAL TRANSLATION MODELS.Zakaria El MaazouziBadr Eddine EL MohajirMohammed Al AchhabAchieving high accuracy in automatic translation tasks has been one of the challenging goals for researchers in the area of machine translation since decades. Thus, the eagerness of exploring new possible ways to improve machine translation was always the matter for researchers in the field. Automatic translation as a key application in the natural language processing domain has developed many approaches, namely statistical machine translation and recently neural machine translation that improved largely the translation quality especially for Latin languages. They have even made it possible for the translation of some language pairs to approach human translation quality. In this paper, we present a survey of the state of the art of statistical translation, where we describe the different existing methodologies, and we overview the recent research studies while pointing out the main strengths and limitations of the different approaches.https://www.scienceopen.com/document?vid=83e44e0b-765e-483d-b050-4d82cb5930d6
spellingShingle Zakaria El Maazouzi
Badr Eddine EL Mohajir
Mohammed Al Achhab
A SYSTEMATIC READING IN STATISTICAL TRANSLATION: FROM THE STATISTICAL MACHINE TRANSLATION TO THE NEURAL TRANSLATION MODELS.
Journal of ICT
title A SYSTEMATIC READING IN STATISTICAL TRANSLATION: FROM THE STATISTICAL MACHINE TRANSLATION TO THE NEURAL TRANSLATION MODELS.
title_full A SYSTEMATIC READING IN STATISTICAL TRANSLATION: FROM THE STATISTICAL MACHINE TRANSLATION TO THE NEURAL TRANSLATION MODELS.
title_fullStr A SYSTEMATIC READING IN STATISTICAL TRANSLATION: FROM THE STATISTICAL MACHINE TRANSLATION TO THE NEURAL TRANSLATION MODELS.
title_full_unstemmed A SYSTEMATIC READING IN STATISTICAL TRANSLATION: FROM THE STATISTICAL MACHINE TRANSLATION TO THE NEURAL TRANSLATION MODELS.
title_short A SYSTEMATIC READING IN STATISTICAL TRANSLATION: FROM THE STATISTICAL MACHINE TRANSLATION TO THE NEURAL TRANSLATION MODELS.
title_sort systematic reading in statistical translation from the statistical machine translation to the neural translation models
url https://www.scienceopen.com/document?vid=83e44e0b-765e-483d-b050-4d82cb5930d6
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